Dendrogram

Centroid Linkage Circular Dark

Centroid method clustering displayed as circular dendrogram

Output
Centroid Linkage Circular Dark
Python
import matplotlib.pyplot as plt
import numpy as np
from scipy.cluster.hierarchy import dendrogram, linkage, set_link_color_palette

np.random.seed(369)

n = 18
labels = [f'N{i}' for i in range(1, n+1)]
data = np.random.rand(n, 6) * 85
Z = linkage(data, method='centroid')

fig_temp, ax_temp = plt.subplots()
set_link_color_palette(['#27D3F5', '#F5276C', '#6CF527', '#F5D327', '#5314E6'])
dn = dendrogram(Z, labels=labels, no_plot=False, color_threshold=0.55*max(Z[:,2]),
                above_threshold_color='#555555', ax=ax_temp)
plt.close(fig_temp)

icoord = np.array(dn['icoord'])
dcoord = np.array(dn['dcoord'])
colors = dn['color_list']

x_min, x_max = icoord.min(), icoord.max()
y_max = dcoord.max()

def to_polar(x, y):
    theta = (x - x_min) / (x_max - x_min) * 2 * np.pi * 0.93 + np.pi * 0.035
    r = y / y_max * 0.5 + 0.45
    return theta, r

fig, ax = plt.subplots(figsize=(10, 10), subplot_kw={'projection': 'polar'}, facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

# Draw rings
for r in [0.55, 0.7, 0.85, 0.95]:
    circle_theta = np.linspace(0, 2*np.pi, 100)
    ax.plot(circle_theta, [r]*100, color='#27D3F5', linewidth=0.5, alpha=0.2)

for ic, dc, color in zip(icoord, dcoord, colors):
    thetas, rs = [], []
    for x, y in zip(ic, dc):
        t, r = to_polar(x, y)
        thetas.append(t)
        rs.append(r)
    
    for lw, alpha in [(4, 0.15), (2, 0.9)]:
        ax.plot([thetas[0], thetas[1]], [rs[0], rs[1]], color=color, linewidth=lw, alpha=alpha)
        ax.plot([thetas[2], thetas[3]], [rs[2], rs[3]], color=color, linewidth=lw, alpha=alpha)
        if thetas[1] != thetas[2]:
            arc_thetas = np.linspace(min(thetas[1], thetas[2]), max(thetas[1], thetas[2]), 45)
            ax.plot(arc_thetas, [rs[1]]*len(arc_thetas), color=color, linewidth=lw, alpha=alpha)

leaf_positions = np.linspace(x_min, x_max, n)
for i, (pos, label) in enumerate(zip(leaf_positions, dn['ivl'])):
    theta, _ = to_polar(pos, 0)
    rotation = np.degrees(theta) - 90 if np.pi/2 < theta < 3*np.pi/2 else np.degrees(theta) + 90
    ha = 'right' if np.pi/2 < theta < 3*np.pi/2 else 'left'
    ax.text(theta, 0.32, label, ha=ha, va='center', fontsize=8, color='white',
            rotation=rotation, rotation_mode='anchor')
    
    color = ['#27D3F5', '#F5276C', '#6CF527', '#F5D327', '#5314E6'][i % 5]
    ax.scatter(theta, 0.45, c=color, s=45, zorder=5, edgecolor='white', linewidth=0.5)

ax.set_ylim(0, 1.02)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.spines['polar'].set_visible(False)
ax.grid(False)

ax.set_title('Centroid Linkage - Circular View', fontsize=14, color='white', fontweight='bold', y=1.08)

plt.tight_layout()
plt.show()
Library

Matplotlib

Category

Statistical

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